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We're here to help you find itThe "Trading Algorithm & Financial Portfolio Optimization with Python" course is designed to equip learners with the skills necessary to apply Python programming to financial markets. It delves into algorithmic trading and portfolio optimization using Python's powerful libraries.
Module 1 lays the foundation by introducing Python and its installation across different operating systems. It guides students through the basics of using Python IDLE and the differences between interactive and scripting modes.
As learners progress, they encounter NumPy and Pandas in Modules 2 and 3, which are critical for numerical and data analysis. Module 4 imparts knowledge on data visualization, a vital skill for interpreting financial data.
Real-world financial data handling is explored in Module 5, while Module 6 focuses on time series analysis with Pandas, essential for historical market data analysis.
Modules 7 and 8 delve deeper into time series forecasting, introducing learners to advanced statistical models like ARIMA.
Module 9 covers foundational finance concepts such as the Sharpe ratio, portfolio optimization, and the Capital Asset Pricing Model (CAPM).
In Module 10, the course transitions into the realm of trading algorithms, exploring strategies, leverage, and hedging, along with portfolio analysis using PyFolio.
Finally, Module 11 provides a practical introduction to Quantopian, a platform for designing and testing trading algorithms.
Overall, this course is a comprehensive journey through the intersection of finance and Python programming, enabling learners to create and optimize trading strategies algorithmically.
This is a Rare Course and it can be take up to 3 weeks to arrange the training.
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♱ Excluding VAT/GST
Classroom Training price is on request
♱ Excluding VAT/GST
Classroom Training price is on request
To ensure that you can successfully undertake the Trading Algorithm & Financial Portfolio Optimization with Python course, the following prerequisites are recommended:
Basic understanding of programming concepts: While you will be introduced to Python, having a grasp of fundamental programming principles will help you to quickly understand and apply Python concepts.
Familiarity with Python: Some experience with Python or another programming language is beneficial, as the course moves into advanced libraries and frameworks built on Python.
Basic knowledge of mathematics and statistics: Concepts such as mean, median, standard deviation, and basic algebra will be useful, especially for understanding financial data analysis and portfolio optimization techniques.
Understanding of financial markets: A general awareness of how financial markets operate, including stocks, bonds, and other investment vehicles, will help in comprehending the application of algorithms in trading.
Interest in data analysis: A keen interest in analyzing and interpreting data will make the learning process more engaging and insightful when working with financial datasets.
Willingness to learn and experiment: A proactive attitude and the readiness to experiment with code and financial concepts are essential to making the most of this course.
These prerequisites are designed to ensure that you have a foundation upon which the course material can build. With these in place, you will be better positioned to grasp the more advanced topics covered in the course.
This course offers comprehensive training in algorithmic trading and portfolio optimization using Python for finance professionals.
Target Audience and Job Roles:
This course equips students with the expertise to craft trading algorithms and optimize financial portfolios using Python, delving into libraries like NumPy and Pandas, and platforms such as Quantopian.
